WSES: HIGH SECURED DATA ENCRYPTION AND AUTHENTICATION USING
WEAVING, ROTATION AND FLIPPING
A. Yesu Raja
1and S. Arumuga Perumal
2 Department of Computer Science, S.T. Hindu College, India E-mail: 1a_yesuraja@yahoo.co.in and 2visvenk@yahoo.co.inAbstract
Data security is the very important part in the network data communication. Avoidance of the information hacking and steeling are very challenging part for network data communication. Now-a-days people are using many encryption and decryption techniques for data security. But all encryption and decryption techniques are having more time occupation or less security for the process. This paper proposed high level security approach to encryption and decryption for data security. Two levels of securities are used in this proposed method. First one is data encryption and the second one is hash value generation. The proposed Weaving based Superior Encryption Standard (WSES) uses a novel weaving based approach. The weaving array generation is done by Elementary Number Theory Notation (ENTN) method. The weaving array has multiple private keys for XOR encryption. After encryption the error value is extracted from the encrypted array and weaving array. This error value is sent to the other side. The novel approach for hash value generation uses the encrypted array. After encryption, the encrypted array is rotated into four degrees and each degree data are converted to vector format and arranged on by one under the vector. Finally a 2D Rotational Encryption Matrix (REM) is obtained. After this process a REM copy is converted to mirror flip and it is need as Flipped Matrix (FM). The FM is concatenated under the REM and converted to vector using the zigzag operation. Finally this process gives two bytes hash value from the vector. This proposed method executes very fast and provide high security. This method is much reliable to small size applications and also used for any type of data security.
Keywords:
Data Security, XOR, WSES, Encryption, Decryption, Hash, ENTN, Weaving, REM, Flipped Matrix
1. INTRODUCTION
Secret sharing schemes have been independently introduced by Blakley [1] and Shamir [2]. In the Shamir’s secret sharing scheme said by, a secret m is divided into n number of pieces m1; . . . ; mn, which satisfies, 1) knowledge of whichever t or more mi pieces makes m easily computable, and 2) knowledge of whichever t-1 or fewer mi pieces leaves m completely undetermined. Shamir’s secret sharing scheme, which is also called as (t, n) secret sharing, can be proven to be information-theoretically secure.
Sahai and Waters [3] are addressed this issue by introduce the notion of Attribute Based Encryption (ABE). The ABE is a new public key based one-to-many encryptions and that encryption standard enables access control over encrypted data using access policies which are associated with private keys [4].
Visual cryptographic scheme (VCS) is a category of secret image sharing schemes. In a threshold (k, n), where k ≤ n, a secret image is encrypted into n shadow images (shadows) by
growing a secret pixel into m sub-pixels. The visual quality of reconstructed image is very poor by the VCS. Another one polynomial-based secured image sharing scheme can recover the distortion levels very less in the secret image, but its decoding process needs Lagrange interpolation [5], [6]. The authors combined the VCS and polynomial-based secured image sharing to design and development by a two-in-one VCS, with different types of decoding options [7], [8]. This two-in-one Visual cryptographic scheme is having two parts, first stage is stacking to see a formless reconstructed image and the second stage is used to reconstruct the secret image perfectly by Lagrange interpolation.
In the symmetric key cryptography, both transmitter and receiver use a same key for encryption and decryption and it needs a secure channel or a trusted third party to exchange the key. In other words, the security of the symmetric key cryptography depends on the way of key exchange to some extent. To avoid this issue, public-key cryptography was used, in which a transmitter and a receiver own different private keys and share a public key. The keys are mathematically related. Encryption and decryption are performed by using the public key and the private key. The security of the public-key cryptography mainly lies on the complexity of the mathematical relationship between the public key and private key [9], [10].
In previous years the author of paper [11] have analyzed exam results from the Data Security course and noticed that students had trouble understanding cryptographic algorithms, which resulted in lower grades on the part of the exam covering this area and consequently the final grades for the exam. The reason for this was the difficulty for students to closely follow the execution of algorithms, because they are too complex to be calculated manually on paper.
In order to help students to better understand the material many teachers in different areas use educational software systems. These systems have a significant presence in engineering sciences, where it is important for students to have practical work in addition to classes. Systems differ significantly depending on the area in which they are used. It is common in hardware related courses to use software simulators in order to avoid the high price of the necessary equipment for the laboratory exercises. In software related areas that teach algorithms, software systems for visual representation of the algorithms [12] are often used for both teaching and laboratory exercises.
communication channels, exchange the secret keys are required to between transmitter and intended receiver. The Advanced Encryption Standard (AES) design implementation utilized 16 map online and offline key expansion. A simple design utilized only eight cores for online key expansion and six cores for offline key expansion. This implementation explores to the data level and task level parallelism. This implementation’s main aim is to reduce the core and increased the workload [14]. Patient health record system is encrypted with Attribute Based Encryption (ABE). It is mainly focus on multiple data owner’s situation. The multiple security domains reduced the key management complexity for owner and user [15].
In cloud security with the involvement of the third party cloud services, a crucial problem is that the identity attribute in the Access Control Policies (ACPS) often reveal privacy-sensitive information about users and leak secret information about the content. The secrecy of the content and the privacy of the users are, thus, not fully confined if the identity attributes are not protected. Further confidentiality, both individual as well as organizational, all process is considered a key requirement in all solutions, it is including cloud services, for Digital Identity Management (DIF) [16].
Radio Frequency Identification security protocols often rely on hash function methods. Some of the applications need protected from collision and some of them do not needing pre-image security. An interesting case is established by keyed Message Authentication Codes (MAC) frequently used in this context. Here, a lightweight hashing method can require less area and then a lightweight block cipher in a Message Authentication Codes mode at a permanent level of offline and online protection. Message Authentication Codes can be also designed using sponge primitives [17].
The most widely used hash function is SHA family, which contains SHA-0, SHA-1, SHA-2 published by National Institute of Standards & Technology (NIST). In the recent years, the cryptanalysts processes have establish collisions on the MD4, MD5 and SHA-0 hashing algorithms. Moreover, a method for discovery SHA-1 collisions with minimum expected amount of work has been published. In this case, NIST decided to hold a public competition for a new Standard Hash Algorithm (SHA-3) in 2007 [18]. After two round competition, 14 candidate algorithms were selected [19].
It was not until recently though that some important work on trivial hash functions has been a performed [20] describes ways of using the PRESENT block cypher in hashing methods of operation and [21] take the approach of designing a committed trivial hash function based on a sponge building [22], [23] resulting in couple of hash functions QUARK and PHOTON.
A hash function is a function that maps a bit sequence of arbitrary length to a fixed-length output. As a rule, three security requirements are mentioned for a hash function. First, it should be pre-image resistant: Given an output (hash value), it should be hard to find an input (message) that would map to this output. Second, it should be second pre image resistance: Given a hash value and a corresponding message, it should be difficult to find another message with the same hash value. Finally, it should be collision resistant: It should be infeasible to find two messages with the same hash value.
2.
PROPOSED ENCRYPTION METHOD
Data security is very important in now a day because most of the important information can be communicate through computer.
Fig.1. Block Diagram for Encryption and Hashing
The communication can be done with locally or World Wide Web. Data steeling is very challenging trouble in the modern society. The encryption can be done the data with fast and more security. Low secured data encryption can be easily decrypting the data with hackers. This paper mainly proposed a novel method of encryption and decryption for data with hashing method. If the information can be changed while the transmission, the hashing signature value also change. If the hashing signature value can be changed, the process will be rejected.
The Fig.1 explains how can be the data encryption and generation of the hash value. Input data can be set into the NN matrix. Generate the matrix using the Elementary Number Theory Notation (ENTN) supported with private key. The private key can be converted near by the prime number. This matrix size can be greater than the input NN message matrix. O/P1, O/P2, O/P3 are representing the three outputs. O/P1 is sending the error value while O/P2 is sending the sign values. The sign values are having – and + signatures. Finally the O/P3 contains hash value. These three outputs are sent to the other side.
Input Message
Set the Data into NN Array
ENTN Using Private Key
Weaving Process
Data Encryption
Error Value Calculation
Classifying the Sign Value
Hash Value Generation
O/P 3 O/P 1
O/P 2 Extracted NN Size Matrix
Flip the NN Size Matrix
Scalable & Flipping
Fig.2. Block Diagram for Decryption
The Fig.2 can be indicating the decryption process of the data. The ENTN can be used to generate the weaving array using the private key. The error values are reconstructed with error and sign value. These are received from client. The reconstructed error value is subtracted with the Weaving Array. After the process, the subtracted value is called the encrypted array. The encrypted array can be converted to decrypted array using with the weaving array.
In addition, the encrypted array can be used to the hash value creation process. After hash value computation, the hash value is matched with the clients hash value. If the hash value is same, the authentication process is successful otherwise the data not successful because may be changed while the data sending.
2.1
KEY MATRIX
Elementary number theory concerning Z = {…,-2, -1, 0, 1, 2,…} of integers and the set N = {0, 1, 2, …} of natural numbers. For any integer and positive integer n, there are unique integers q and r such that 0 ≤ r < n and a = qn + r.
The value q
a n is the quotient of the division. The value r = a mod n is the reminder (or residue) of the division. We have that n/a if and only if a mod n = 0.The integers can be divided into n equivalence classes according to their reminders modulo n. The equivalence class modules n contain an integer, ai as following Eq.(1).
a a p n kni p n i
1 1 0 (1)
PWDn
zmod ,
where,
kN - Assume k = [0, a]
n - Any prime number using single byte
a - find the nearby prime number for z (Greater than z) i - Row of elementary number series (assume I = [0, N]) kN - Natural Number
2.2
HORIZONTAL FLIPPING
The Secret Message (SM) has been converted into NN size of matrix it is Secret Message Array (SMA). The dimension of private key matrix is 2 * Height of secret message. Divide the private key matrix into two equal parts A and B. The second part matrix B has horizontally flipped using the Eq.(2).
iW j
B
Bi,j , B1 (2) where,
i [0, WH – 1]; j [0, WB – 1]
WH - B Matrix Height; WB - B Matrix Width.
2.3
WEAVING MATRIX
Weaving process has very important in this proposed method. The private key is used to encrypt the input message. The Weaving Matrix (WM) contains multi range of keys. The weaving matrix is constructed by using the following Eq.(3).
1 , m od 1 2 , m od & , 1 , m od 0 2 , m od & , 0 , m od 1 2 , m od & , 0 , m od 0 2 , m od & , , j i j j i j i j j i j i j j i j i j j i j i A B B A WM (3) 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 A A A A A A A A A A A A A A A A A A A A A A A A A A 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 B B B B B B B B B B B B B B B B B B B B B B B B B B 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 A B A B A B A B A B A B A B A B A B A B A B A B A WM O/P 1 ENTN Using Private KeyWeaving Process
Add Sign Value into Error Value
Encrypted Array
Decrypted Array
Hash Value Generation
Scalable & Flipping
Zig Zag Operation
Detection Process
O/P 2
O/P 3
Above the matrix represents a sample structure of constructing WM from A and B. The matrix A is represented the SMA size of matrix which extracted from the Eq.(1). Matrix B represents flipped matrix from the matrix A. The A and Bare the same size of SMA. After flipping process the matrix B can be weaving on the matrix A based on Eq.(3). The matrix WM represents sample structure for Weaving Matrix. For example the matrix A size is 5 5 and matrix B size is 5 5. After applying the weaving process WM size is also 5 5.
The WM values are having large numeric value. So the normalization process is applied to restrict the values PK within 0 to 255. The values are constructed by the Eq.(4).
WM MV maxR MV WM fix
PKi j i j
,
, (4)
where,
R - Maximum storage capacity of bytes data types MV - Maximum value in WAM matrix
PKi,j- Private Key Weaving
2.4
DATA ENCRYPTION
This encryption standard encrypted the original image and data using two steps of private keys. First one is gives from user and another one, multi private keys is automatically created. The size of private key matrix is same to the secrete message matrix size. The XOR operation is used for the data encryption. This type of data encryption is highly secured and reliable. The TLX and TLY are defining the direction of the encryption process.
0, 1;1,0
TLX
1,0;0,1
TLY
SM PKTL iTL j
XOR
EDi,j i,j, Y 0 , X 0 (5)
ED PKTL k iTL k j
XOR
EDMi,j i,j, Y , X
where,
k [1, 3], TL - Template
i [0, SM Height]; j [0, SM Width] EDM - Encrypted Data Matrix
2.5
ERROR VALUE CALCULATION
Subtraction of the encrypted data from weaving array is called error value. The extracted values are sent to the server by client. The real encrypted data is not sent to the server. The error values are the one and only component used to decrypt the secrete message. The error values separated using the Eq.(6).
j i j
i j
i WM EDM
ET, , , (6)
The ET values are distributed from negative numbers to positive numbers. This type of format takes higher memories. To control two byte data memory into one byte data memory the negative and positive sign value are extracted from ET data.
Otherwise ET SBMi j i j
1
0 ,
0 ,
, (7)
The Sign Bit Matrix (SBM) has 0 and 1 values. The matrix value 0 represents negative sign and 1 represents positive sign.
ij ji absET
ED, , (8)
After applying the absolute function on the ET, The ED is generated without the sign. The ED and SBM are sending to the server by client.
3.
PROPOSED HASH VALUE CREATION
The hash value is created after the encrypted data is created. A hash value is sending form client to server. This hash value is created from the real encrypted data. If the real data is changed during sending time, the server computes a different hash value and compared with client side hash value. This hash value is used against the replay attack.
3.1
ROTATIONAL ENCRYPTED MATRIX
Encrypted matrix can be rotated into four directions respectively 00, 900, 1800 and 2700 for the hash value creation. The directional matrix for rotation can be defined as follows.
cos sin
sin cos R
The column rotation based matrix multiplication is achieved using the Eq.(9).
y x y
x
cos sin
sin cos
(9)
The following directional templates are used for the multi directions such as 900, 1800 and 2700 respectively.
90Template → [0, -1; 1, 0]
180Template → [-1, 0; 0, 1]
270 Template → [0, 1; -1, 0]
After rotation process four 2D matrixes related with 00, 900, 1800 and 2700 are obtained. The 2D matrixes can be converted into vector format. After vector conversion four vectors are generated. These four vectors can be arranged one by one. The REM can be used to explain, how to rearrange the vectors from multi directional rotational matrix into 2D matrix named as Rotational Encrypted Matrix (REM). The following four directional matrixes can be represented the sample structure of multi directional rotational matrix.
C F I
B E H
A D G
I H G
F E D
C B A
90 0
G D A
H E B
I F C
A B C
D E F
G H I
270 180
G D A H E B I F C
A B C D E F G H I
C F I B E H A D G
I H G F E D C B A
REM
In the REM matrix first row represents the vector of 00 2D matrix, second row represents the linear array of 900 2D matrix, third row represents the linear array of 1800 2D matrix and fourth row represents the linear array of 2700 2D matrix. The 4
N dimensional REM is achieved from the multi directional rotational encrypted matrixes.
3.2
HORIZONTAL MIRROR FLIPPING
The REM is undergone the horizontal mirror flipping process. The output matrix of flipping process FM is jointed at the bottom of REM.
The flipping process is performed using the Eq.(10).
iW j
REM
FMi,j , B1, (10) where,
i[0, WH – 1] j [0, WB– 1]
WH - REM Height; WB - REM Width
The FM is concatenated with the REM and it is named as Flipped Rotational Encrypted Matrix (FREM). This process can be represented by the following matrix. The dimension of the concatenated matrix is 2WHWB.
C F I B E H A D G
I H G F E D C B A
G D A H E B I F C
A B C D E F G H I
G D A H E B I F C
A B C D E F G H I
C F I B E H A D G
I H G F E D C B A
FREM
The above matrix represents the first four rows are REM matrix and remaining four rows are FM matrix.
3.3
ZIGZAG VECTOR CONVERSION
The 2D FREM matrix is converted into vector form for the hash value generation using zigzag scanning method. This can be illustrated in the Fig.5(a).
(a)
0 1 2 3 4 5 … 80 A B G I D C … C
(b)
Fig.3. (a) Flow of zigzag in the FREM (b) Vector Conversion Using Zigzag
In the Fig.3(a) 2D matrix has been converted into a Vector Matrix Fig.3(b) using zigzag operation and it is called as Zigzag Vector Matrix (ZVM). The Fig.3(a) indicates the flow of the data which shows in 2D matrix. The Fig.3(b) indicates the rearranged data from Fig.3(a) matrix. The rearrangement Fig.3(b) matrix is converted into vector data.
3.4
TWO BYTE HASH VALUE CREATION
Zigzag Vector Matrix contains 0 to n-1 indexes. In vector each value is having one byte memory size. If the hash value is in one byte memory size, the hash value easily hacks with the attacker. So this method is created with two byte memory hash value.
Fig.4. Sample Structure for Hash Value Generation
The Fig.4 indicates how to generate the two bytes single hash value. Two bytes memory hash value is created using the Eq.(11).
IntF
ZVM
0,
ZVM
1,
IntF
ZVM
2,
ZVM
3
XOR
A
(11)
x
y
x
y
IntF
,
8
,
,
1
XOR
A
IntF
ZVM
iZVM
iA
(12)
4
,
1
and
mod
,
2
0
n
i
i
where,
A - XOR Result
IntF - Integration Function to merge the sequence two bytes into a two bytes data.
ZVM - Input Vector
XOR() - Function to perform exclusive OR operation << - Left Shift operator
n - Total number of Input Vectors
4.
ANALYSIS
This experimental analysis is performed based on the time factor for various sizes of data. This time factor performance is computed with the system CPU 2.13GHz with 2GB RAM. This time factor analysis is compared with the different size of data bytes. The bytes data are compared by the different types of methodologies namely Advance Encryption Standard (AES), Data Encryption Standard (DES), Blowfish (BF) [24] and the proposed Weaving based Superior Encryption Standard (WSES).
Table.1. Time Taken for Encryption
Data Size (bytes)
Encryption time taken (seconds)
Methods
AES DES BF WSES
7200 6 12 8 0.4
154000 2 20 10 0.8
203000 9 25 12 1
351000 12 40 17 2
476000 15 52 22 3
589000 17 64 25 4
718000 20 77 30 5
1222000 32 130 48 9
1715000 42 180 66 14
3156000 76 329 119 30
The Table.1 indicates the time taken of various methods for the data encryption process. Numbers of various bytes data are used in the time calculation process. The Fig.5 indicates the graphical representation of time taken for the various data encryption processes.
Fig.5. Time taken graphical representation for data encryption
Decryption is the reverse process of the encryption method. In the encryption real data could be changed to different format. So the encrypted data can be converted to real data and it is
called decryption. The decryption process time taken for WSES method is very less when compared with the existing methods.
Table.2. Time Taken for Decryption
Data Size (bytes)
Data Decryption
Methods
AES DES BF WSES
7200 2 8 4 0.3
154000 4 16 6 0.7
203000 4 21 7 1
351000 8 36 13 2
476000 11 48 18 3
589000 13 60 21 4
718000 16 73 26 5
1222000 28 126 44 9 1715000 38 176 62 13 3156000 72 325 115 29
The Table.2 indicates the time taken of various methods for the data decryption process. Number of various bytes data are using in the time calculation process. The Fig.6 indicates the graphical representation of time taken analysis for the various data decryption process.
Fig.6. Time taken graphical representation for data decryption
Total time taken is calculated for the data encryption and decryption process individually. In this encryption and decryption methods, time calculation is performed using 10 different sizes of data. The Encryption total time taken Fig.7 is computed by summing up the time consumption of each different size of data to do encryption process.
0 50 100 150 200 250 300 350
Tim
e
Ta
k
en
(S
ec
o
n
d
s)
Data Size (Bytes)
Encryption Time Taken Analysis
AES DES BF WSES
0 50 100 150 200 250 300 350
Tim
e
Ta
k
en
(S
ec
o
n
d
s)
Data Size (Bytes)
Decryption Time Taken Analysis
Fig.7. Encryption Total Time Taken Analysis Chart
Fig.8. Decryption Total Time Taken Analysis Chart
The Fig.8 shows the Decryption total time taken for 10 difference type of data. The Decryption total time taken is computed by summing up the time consumption of each different size of data to do decryption process. From the Fig.7 and Fig.8 it can be easily understand that the proposed WSES method is paramount in encryption methods.
5.
CONCLUSION
This is used for network data communication to any type of data security. This security system has the novel approach of encryption based Weaving Algorithm and also it proposes a new Hash value generation method for high secured authentication. The proposed security system avoids information hacking and steeling. If the information is hacked and has committed any change, the hash value also changed. This Weaving Algorithm is more secured and speed than the earlier versions of encryption techniques. The proposed Encryption is 179.16% faster in execution and Decryption is 211.78% faster than the existing AES technique. The proposed security system is more suitable
for the applications wherever high security as well as higher execution speed is required.
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